Decision-Making Tool for Optimal Management of AIS

This project developed a decision-making tool to help AIS managers, counties, and other agencies prioritize their resources for optimal prevention and intervention of AIS, specifically zebra mussels and starry stonewort (AIS Explorer). 

Effective management of aquatic invasive species (AIS) in complex and dynamic systems, considering variable needs, values, and constraints, has proven difficult. AIS managers at the local and state levels urgently need science-based tools to inform planning and decision-making. Researchers at MAISRC worked to develop models that forecast the invasion of zebra mussels and Eurasian watermilfoil in Minnesota at the lake level. The models are subjected to strict verification and cross-validation to ensure confidence in model predictions. The risk scores for each waterbody is then used to inform AIS management optimization models at the county level. Optimization models are a useful approach to identify a set of actions that make the best use of available resources while achieving a desired outcome. Therefore, in addition to the risk scores, values and management objectives such as types of lakes to prioritize for prevention (e.g. All lakes equally? Large/popular lakes?) researchers also incorporated the allocation of available funds and strategic locations for prevention and control activities to reduce the risk of new AIS introductions within each county. Similarly, cumulative risk models were developed to help inform statewide allocation of the County AIS Prevention Aid, compared to the current approach of total boat ramps and parking spots. Local and state AIS managers were engaged throughout the project to ensure consistency with management goals and realities. 

Progress:

MAISRC researchers developed an online dashboard—AIS Explorer—that both forecasts the introduction risk of aquatic invasive species to individual waterbodies and provides decision-making support for optimizing watercraft inspection efficacy. Since its launch in 2020, the dashboard has become an important resource in the planning toolkit of many county and local government resource managers. Thanks to feedback from users, AIS Explorer expanded in 2021 to include Tribal boundaries, updated lake names, and improved usability. In 2022, users can look forward to the incorporation of new features and updated data.

Findings:

We used a big data approach to combine hydrologic connectivity and boat movement to create a multiplex metacommunity model for both zebra mussel and Eurasian watermilfoil. We found that the hydrological corridors are important pathways of spread, even more so that previous research has suggested. While overland dispersal of AIS via boater movement is still a significant factor, additional management strategies should be developed to include intervention of hydrological pathways.

Using connectivity networks of boater movement, we developed county-based AIS management optimization models that prioritize inspection locations that will intercept the highest number of ‘risky boats’ (e.g. moving from infested to uninfested lakes). We piloted the models in Crow Wing, Ramsey, and Stearns Counties and had a very productive collaboration with county managers and citizen advisory boards during the development and evaluation for each. Ultimately, the application of this approach was well received and helped inform allocation of their inspection hours at the county level (for example, Crow Wing County).

Dissemination and usability of the models was a priority of this project. We created online tools to 1) visualize the spread risk for zebra mussels and Eurasian watermilfoil based on model predictions made in Activity 1, and 2) visualize and modify the decision optimization model at the county level based on management thresholds or funding availability.

Project manager: Nick Phelps

Funded by: Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on Minnesota Resources

Project start date: 2017

Project end date: 2019

Resources

AIS Explorer handout (PDF)